Nothing
library(grImport)
data <- read.table(textConnection('
name ev.trt n.trt ev.ctrl n.ctrl
1 Auckland 36 532 60 538
2 Block 1 69 5 61
3 Doran 4 81 11 63
4 Gamsu 14 131 20 137
5 Morrison 3 67 7 59
6 Papageorgiou 1 71 7 75
7 Tauesch 8 56 10 71
'
), header=TRUE)
cer <- w.approx.cer(data[["ev.ctrl"]], data[["n.ctrl"]])
sm <- "RR"
if (requireNamespace("meta", quietly = TRUE)) {
## Calculate the pooled OR or RR point estimate, we use meta package here
m <- with(data,
meta::metabin(ev.trt, n.trt, ev.ctrl, n.ctrl, sm=sm))
point <- exp(m$TE.random) # meta returns outcomes on the log scale
} else {
## Calculated Random Effects RR, using the meta package
point <- 0.5710092
}
ier <- calc.ier(cer, point, sm)
u <- uplift(ier, cer, F)
plot(u, fig.title="Example", fig.cap="Example from rMeta")
## Test with zero CER
data <- read.table(textConnection('
name ai n1i ci n2i days
1 Zarate 6 15 0 15 1
2 Murrough 30 47 0 25 1
3 Zarate 13 18 0 18 1
4 Lapidus 8 18 0 18 1
5 Diazgranado 10 18 0 18 1
'), header=TRUE)
# cer <- w.approx.cer(data$ci, data$n2i)
## Draw documentation graphics
## u <- uplift(ier, cer, F)
## pdf("man/figures/green.pdf", 8, 10)
## plot(u, fig.title="Example", fig.cap="Example from rMeta")
## dev.off()
## png("man/figures/green.png", 800, 1000)
## plot(u, fig.title="Example", fig.cap="Example from rMeta")
## dev.off()
## u <- uplift(ier, cer, T)
## pdf("man/figures/red.pdf", 8, 10)
## plot(u, fig.title="Example", fig.cap="Example from rMeta")
## dev.off()
## png("man/figures/red.png", 800, 1000)
## plot(u, fig.title="Example", fig.cap="Example from rMeta")
## dev.off()
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